Data Science Fundamentals with Python

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Data Science Fundamentals with Python

PYT-316

In this hands-on course, learn how to use the Python scientific stack to complete common data science tasks. We’ll covers the tools and concepts you need to effectively process data, including data crunching, visualization, machine learning, image processing, NLP and more.

course topics

All topics will be covered by solving exercises in class.

Day 1

  • Data science intro
  • Overview of Python & Scientific Python
  • Working with Jupyter notebooks
  • numpy essentials (arrays – matrices, indexing, ufuncs)
  • Loading and exploring data with Pandas (CSV, clean, group by, merge, time series)
  • Visualization with Pandas and matplotlib
  • Installing third party packages using the conda package manager

Day 2

  • Machine learning with scikit-learn (Classification, regression, training utilities, saving models)
  • NLP (Natural language processing) with spaCy
  • Deep learning with keras
  • Image processing with OpenCV
Prerequisites

A working knowledge of the Python programming language.

A laptop with Anaconda (Python 3.6) distribution installed.

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